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Raster lidar data visualizations for interpretation of microrelief structures dr. Žiga Kokalj ZRC SAZU Centre of Excellence for Space Sciences and Technologies.

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Presentation on theme: "Raster lidar data visualizations for interpretation of microrelief structures dr. Žiga Kokalj ZRC SAZU Centre of Excellence for Space Sciences and Technologies."— Presentation transcript:

1 Raster lidar data visualizations for interpretation of microrelief structures
dr. Žiga Kokalj ZRC SAZU Centre of Excellence for Space Sciences and Technologies – Space-Si

2 Why different visualizations?

3 Lidar and past cultural landscapes
forest cover in Europe is growing Slovenia: 39% --> 60% in the last century DEM’s and DSM’s are mainly provided by lidar operators or national mapping authorities they are not optimised for archaeological detection or interpretation DTM – DSM advanced visualisation is rarely used

4 Visualizations simplify interpretation of features
there is more to visualizations than shaded relief interpretation based solely on shaded relief has a big potential to miss important archaeological features (Challis et al Antiquity)

5 Visualizations 1 Analytical hill-shading 2 PCA of hill-shadings
3 Colour cast 4 Trend removal 5 Slope gradient 6 Sky view factor 7 Openess 8 Solar insolation Kokalj et al Antiquity. Kokalj et al Visualizations of lidar derived relief models.

6 Tonovcov grad one of the largest and most important Late Antiquity settlements in the south-eastern Alps 3 early Christian churches from the 5th century Foto: Željko Cimprič

7 Foto: Slavko Ciglenečki

8 Digital orthophoto 50 m

9 Lidar survey Scanning Data processing scanner type Riegl LMS-Q560
platform helicopter date 4th and 16th March 2007 swath width 60 m flying height 450 m average last and only returns per m2 on a combined dataset 11.2 Data processing method REIN (Kobler et al. 2007) spatial resolution of the final elevation model 0.5 m

10 1 Hill-shading the most commonly used technique (Yoëli Kartographische Nachrichten) greyscale colour table – enhances the perception of morphology standard: azimuth at 315°, sun elevation at 45° surface is illuminated by a direct light constant for the entire dataset

11 Shaded relief 315° 45° 50 m Lidar Data Copyright
Walks of Peace in the Soča Region Foundation 50 m 315° °

12 Hill-shading easy to compute and interpret
included in standard GIS software reveals features with low light source on flat areas dark shades and brightly lit areas linear structures parallel to the light source

13 Low light shading 315° 45° 5° 50 m Lidar Data Copyright
Discovery Programme 50 m 315° 45°

14 Illumination effects

15 Typical ridge and furrow case study
Lidar Data Copyright Infoterra Global Ltd 100 m 315° 45° 45°

16 Hill-shading in multiple directions – RGB
50 m RGB 0°, 337,5°, 315° °

17 2 PCA of hill-shadings summarizes information
typically over 99% in the first three components Devereux et al Antiquity. 16 hill-shaded images (100 %) first 3 coponents (> 99 %)

18 PCA of hill-shadings - RGB
50 m °

19 PCA of hill-shadings – bands 1 and 2
50 m °

20 PCA of hill-shadings removes redundancy
does not provide consistent results with different datasets

21 3 Colour cast histogram manipulation, colour ranging
limits the range of displayed values Challis Archaeological Prospection.

22 Colour cast 280 m 1220 m 190 m 270 m 100 m

23 Colour cast useful in flat terrain
retains the display of original elevation data easy to interpret completely fails in rugged terrain extensive manipulation is needed

24 4 Trend removal (LRM) remove the trend in data so only small scale features remain removes the height variation of “global” features 280 m 5 m -5 m 240 m

25 Trend removal (LRM) several methods to assess the trend: averaging
median smoothing Gaussian smoothing improvement with a “purged DEM” (Hesse Archaeological Prospection)

26 Trend removal (LRM) 280 m 1 m 270 m -1 m 50 m Gaussian trend removal
100 m 50 m Gaussian trend removal

27 Trend removal (LRM) can be used as input to other methods
works extremely well with gentle slopes level of smoothing introduces artefacts (e.g. artificial banks and ditches)

28 5 Slope gradient the first derivative of a DEM
inverted greyscale retains relief representation Doneus et al BAR International Series.

29 Slope gradient 90° 50 m

30 Slope gradient easy to compute and interpret
included in standard GIS software works well in combination with hill-shading works well on most types of terrain retains saturated areas additional information needed for interpretation

31 6 Sky View Factor determines the size of the visible sky
elevation angle is determined into multiple directions and to the given distance considers a hemisphere only values between 0 and 1 Kokalj et al Antiquity.

32 Sky View Factor

33 Sky View Factor 1 50 m m (20 px)

34 Sky View Factor 1 0.6 50 m m (20 px)

35 SVF – Noisy data 16 10 m (10 px) 100 m Lidar Data Copyright
State Office for Cultural Heritage Baden-Wurttemberg 100 m m (10 px)

36 Anisotropic SVF 1 0.8 16 10 m (20 px) 100 m Lidar Data Copyright
Janus Pannonius Archaeology Museu 100 m m (20 px)

37 Sky View Factor no saturations
clear distinction between protruding features and depressions particularly useful for complex features helps with noisy data intuitive “washout effect” on very flat terrain with very low protruding features

38 7 Openness quantifies the degree of unobstructedness of a location
very similar to SVF positive and negative Doneus Remote Sensing.

39 Comparison SVF - Openness
negative openness SVF positive openness

40 Comparison SVF - Openness
positive openness SVF

41 Openness – positive 95° 50 50 m m (20 px)

42 Openness – negative 95° 50 50 m m (20 px)

43 Openness no saturations enhances concavities and convexities
useful for complex features completely removes general topography useful for automatic detection the same value on different slopes negative openness not very intuitive to interpret

44 8 Solar insolation amount of the solar energy received at the surface
direct, diffuse and global solar insolation Challis et al Archaeological Prospection.

45 Diffuse solar insolation

46 Global solar insolation

47 Solar insolation preserves a sense of general topography
suitability of land for human activities complex and time consuming calculations numerous options can confuse the user “washout effect” on very flat terrain

48 There‘s more?!!! Planimetric and profile curvature
Contextual filtering edge detection (Laplacian, Sobel’s, Rober’s, Prewitt, Frei and Chen…)… Lambertian relief shading Multidirectional oblique-weighted (MDOW) shaded relief Cumulative visibilty Local dominance Accessibility (Miller 1994) Multi Scale Integral Invariant (Mara 2012)

49 Multi Scale Integral Invariant
50 m 8

50 What to use?

51 What to use? depends on: data collection and processing terrain

52 9 A solution? a combinaton of hillshade, slope severity and SVF

53 Recording… what?

54 Visualizations for scientific publications
because several factor have a big influence on how features are displayed it is imperative to include at least the following into the description of an image: visualization method colour legend data range data stretch type

55 Some help http:\\
Relief Visualization Toolbox standalone and IDL code ArcGIS toolbox hill-shading in 16 directions, PCA, minimum, maximum and a range of values for hill-shadings, slope severity, simplified version of a solar insolation calculation tool simplified version of trend removal. Lidar Visualisation Toolbox – standalone

56 References Kokalj, Ž., Oštir, K., Zakšek, K Application of sky-view factor for the visualization of historic landscape features in lidar-derived relief models. Antiquity 85, 327: Kokalj, Ž., Zakšek, K., Oštir, K Visualizations of lidar derived relief models. In: Opitz, R., Cowley., D. (eds) Interpreting archaeological topography – airborne laser scanning, aerial photographs and ground observation. Pp Štular, B., Kokalj, Ž., Oštir, K., Nuniger, L Visualization of lidar-derived relief models for detection of archaeological features. Journal of Archaeological Science 39: Yoëli, P Analytische Schattierung. Ein kartographischer Entwurf. Kartographische Nachrichten 15: Devereux, B.J., Amable, G.S., Crow, P Visualisation of LiDAR terrain models for archaeological feature detection. Antiquity 82, 316: Challis, K Airborne laser altimetry in alluviated landscapes. Archaeological Prospection 13, 2: Challis, K., Kokalj, Ž., Kincey, M., Moscrop, D., Howard, A.J Airborne lidar and historic environment records. Antiquity 82, 318: Hesse R LiDAR-derived Local Relief Models - a new tool for archaeological prospection. Archaeological Prospection 17, 2: Doneus, M., Briese, Ch Full-waveform airborne laser scanning as a tool for archaeological reconnaissance. In: "From Space To Place. Proceedings of The 2nd International Conference On Remote Sensing In Archaeology", Bar International Series, 1568 (2006), , December 2006. Doneus, M Openness as visualization technique for interpretative mapping of airborne LiDAR derived digital terrain models. Remote Sensing 5:

57 Thank you for your attention. ziga. kokalj@zrc-sazu. si http:\\iaps

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